Result: Multi-objective sensor planning for efficient and accurate object reconstruction

Title:
Multi-objective sensor planning for efficient and accurate object reconstruction
Source:
Applications of evolutionary computing (Coimbra, 5-7 April 2004)Lecture notes in computer science. :312-321
Publisher Information:
Berlin: Springer, 2004.
Publication Year:
2004
Physical Description:
print, 12 ref
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Centro de Investigación Científica y Educación Superior de Ensenada, División de Física Aplicada, EvoVisión Lab, Mexico
ISSN:
0302-9743
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.15735468
Database:
PASCAL Archive

Further Information

A novel approach for sensor planning, which incorporates multi-objective optimization principals into the autonomous design of sensing strategies, is presented. The study addresses planning the behavior of an automated 3D inspection system, consisting of a manipulator robot in an Eye-on-Hand configuration. Task planning in this context is stated as a constrained multi-objective optimization problem, where reconstruction accuracy and robot motion efficiency are the criteria to optimize. An approach based on evolutionary computation is developed and experimental results shown. The obtained convex Pareto front of solutions confirms the conflict among objectives in our planning.